文献类型：期刊文献

英文题名：Exponential Stability of Periodic Solutions for Inertial Type BAM Cohen-Grossberg Neural Networks

作者：Miao, Chunfang[1];Ke, Yunquan[1]

机构：[1]Shaoxing Univ, Dept Math, Shaoxing 312000, Zhejiang, Peoples R China

年份：2014

卷号：2014

外文期刊名：ABSTRACT AND APPLIED ANALYSIS

收录：SCI-EXPANDED(收录号：WOS:000336588600001)、、Scopus(收录号：2-s2.0-84902193516)、WOS

基金：This work is supported by the Natural Science Foundation of Zhejiang Province (no. Y6100096).

语种：英文

外文摘要：The existence and exponential stability of periodic solutions for inertial type BAM Cohen-Grossberg neural networks are investigated. First, by properly choosing variable substitution, the systemis transformed to first order differential equation. Second, some sufficient conditions that ensure the existence and exponential stability of periodic solutions for the system are obtained by constructing suitable Lyapunov functional and using differential mean value theorem and inequality technique. Finally, two examples are given to illustrate the effectiveness of the results.